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tensor.news grades benchmarks and tags model claims by evidence status. Every fact carries a source record and provenance. Scores are framed as task performance under a disclosed harness, never as deployed capability.

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DeepSeek-V3 vs Llama 3.1-405B

Verdict

DeepSeek-V3 leads 6–4 across 11 shared benchmarks.

DeepSeek-V3 6 · Llama 3.1-405B 4 · 1 tied · higher isn't always better — see caveats.

Per-benchmark head-to-head

DeepSeek-V3Llama 3.1-405B
  • 93.73
    ARC AI2
    93.73
  • 83.33
    BBH
    77.2
  • 42.05
    GPQA diamond
    34.55
  • 85.2
    HellaSwag
    85.6
  • 64.85
    MATH level 5
    49.77
  • 82.93
    MMLU
    79.33
  • 15.75
    OTIS Mock AIME 2024-2025
    9.63
  • 69.4
    PIQA
    71.8
  • 2.68
    SimpleBench
    7.6
  • 82.9
    TriviaQA
    82.7
  • 70.4
    Winogrande
    78.4
A higher number is not always a better model. Each score is task performance under a disclosed harness, and some of these benchmarks are saturated or scored under mixed harnesses. Follow any benchmark to its integrity grade before reading a win as decisive.

Follow the record

These models

  • DeepSeek-V393.73
  • Llama 3.1-405B93.73

DeepSeek-V3 vs …

  • vs PowerMoE-3b
  • vs Claude Fable 5
  • vs GPT-5.5
  • vs Gemini 3.1 Pro
  • vs phi-3-small 7.4B

Llama 3.1-405B vs …

  • vs PowerMoE-3b
  • vs Claude Fable 5
  • vs GPT-5.5
  • vs Gemini 3.1 Pro
  • vs phi-3-small 7.4B